Quantum technology for military applications Sarthak Nahar, Divyam Pithawa, Vivek Bhardwaj, Romil Rawat, Anjali Rawat, Kiran Pachlasiya Quantum Computing in Cybersecurity, 2023 The concepts of quantum physics are applied in technological applications through quantum technology (QTech). Generally speaking, QTech has not yet matured, but it may have substantial effects on future military communications, encryption, and sensing, as well as congressional oversight, authorization, and budgets. A new and potentially revolutionary field called quantum technologies could have an impact on many aspects of daily life. The defence and security industry, as well as military and government organizations, are interested in quantum technologies because they have two unique applications. This paper examines and maps the potential military applications of QTech and serves as a springboard for further investigation into morality, military and governmental strategy, decision-making, and policy as well as assessments of international peace and security. In military applications, quantum technologies create new capabilities, boost efficiency and accuracy, and pave the way for “quantum warfare” in which new military doctrines, plans, rules of engagement, and moral principles must be devised. These technologies are still largely in the experimental stage. Quantum sensing may have military or commercial applications within the next few years. Even while some minor commercial deployments of quantum communication technologies have already been realised, the most advantageous military uses are still many years distant. Similar to this, quantum computers may have specialized uses in the future, but any such uses are most likely at least ten years away. China is now advancing quantum communication while the United States is currently leading the world in the creation of quantum computing (Qcomm).
Organ trafficking on the dark web-the data security and privacy concern in healthcare systems Romil Rawat, Bhagwati Garg, Vinod Mahor, Shrikant Telang, Kiran Pachlasiya, Mukesh Chouhan Internet of Healthcare Things Machine Learning for Security and Privacy, 2022 On the dark web (DW), criminal's are technologically knowledgeable so security agencies must keep up to speed with all data sources in endeavors to find criminals and identify their movement. It has gotten progressively harder to follow this area and monitor criminals and terrorists, as they find and grow new approaches underground for their online activity. Due to the shortage and trouble of safeguarding transplantable organs, patients should normally look out for extensive harvesting for a long time to get a coordinating kidney and crucial organs. This restricted accessibility has made an unlawful commercial center for well-off beneficiaries to try not too considerable delay times. Agents organize such organ transplants and gather the greater part of the installment utilizing cryptocurrency that is now and then directed to finance other criminal operations. To gather and dispense installments at abroad areas, they generally resort to money laundering for finding the money at worldwide spots without being seen by security agencies. With the ease Internet getting to show up in a portion of the influenced nations, online activities of organ trading at the hidden world of DW are utilized to wrongfully exchange human vital body parts. Due to the strictness and limitation of storing and preserving vital organs, the patients always require fresh donors of organs, which could be transplanted to needy people. This waiting time sometimes proves to be life-threatening for patients. To overcome the disastrous situations, the illegal techniques are called using agents who coordinate among donor and receiver by the exchange of money, but at a secret place, because the trade is illegal in most of the countries. So, it's like a covert mission to take both the persons, where safe operation is done, doctor, who is also part of illegal organ trade. Nonetheless, interviewees of one investigation expressed that even though purchasers pay more, vendors get far less for their organs. Also, a few beneficiaries will in general become intermediaries at a later stage. Numerous cases examined illegal trading of organ exchanges have found, the dealers crumble after concealed deals and are exposed to social disgrace so they at last lament their deal in 94% of the cases. This Propose work presents a building structure to evaluate the danger of the human organ trafficking trade at the online social stage and to distinguish online presence and channels of correspondence medium.
IoT and Artificial Intelligence Techniques for Public Safety and Security Smart Urban Computing Applications, 2022
SCNTA: Monitoring of Network Availability and Activity for Identification of Anomalies Using Machine Learning Approaches Romil Rawat, Bhagwati Garg, Kiran Pachlasiya, Vinod Mahor, Shrikant Telang, Mukesh Chouhan, Surendra Kumar Shukla, Rina Mishra International Journal of Information Technology and Web Engineering, 2022 Real-time network inspection applications face a threat of vulnerability as high-speed networks continue to expand. For companies and ISPs, real-time traffic classification is an issue. The classifier monitor is made up of three modules: Capturing_of_Packets (CoP) and pre-processing, Reconciliation_of_Flow (RoF), and categorization of Machine Learning (ML). Based on parallel processing along with well-defined interfacing of data, the modules are framed, allowing each module to be modified and upgraded separately. The Reconciliation_of_Flow (RoF) mechanism becomes the output bottleneck in this pipeline. In this implementation, an optimal reconciliation process was used, resulting in an average delivery time of 0.62 seconds. In order to verify our method, we equated the results of the AdaBoost Ensemble Learning Algorithm (ABELA), Naive Bayes (NB), Decision Tree (DT), K-Nearest Neighbor (KNN), and Flexible Naive Bayes (FNB) in the classification module. The architectural design of the run time CSNTA categorization (flow-based) scheme is presented in this paper.
Analyzing Newspaper Articles for Text-Related Data for Finding Vulnerable Posts over the Internet That Are Linked to Terrorist Activities Romil Rawat, Vinod Mahor, Bhagwati Garg, Shrikant Telang, Kiran Pachlasiya, Anil Kumar, Surendra Kumar Shukla, Megha Kuliha International Journal of Information Security and Privacy, 2022 One of the most critical activities of revealing terrorism-related information is classifying online documents.The internet provides consumers with a variety of useful knowledge, and the volume of web material is increasingly growing. This makes finding potentially hazardous records incredibly difficult. To define the contents, merely extracting keywords from records is inadequate. Many methods have been studied so far to develop automatic document classification systems, they are mainly computational and knowledge-based approaches. due to the complexities of natural languages, these approaches do not provide sufficient results. To fix this shortcoming, we given approach of structure dependent on the WordNet hierarchy and the frequency of n-gram data that employs word similarity. Using four different queries terms from four different regions, this approach was checked for the NY Times articles that were sampled. Our suggested approach successfully removes background words and phrases from the document recognizes connected to terrorism texts, according to experimental findings.
RECENT SCHOLAR PUBLICATIONS
AI-Driven Flexibility in Next-Generation Communication Systems A Review of Models, Confrontation, and Tomorrow’s Directions SS Kiran Pachlasiya International Journal of Scientific Research in Engineering and Management … , 2025 2025
Density Based Smart Traffic Control System Using Canny Edge Detection SR Likhita Devi Ravipati Kiran Pachlasiya International Journal of Scientific Research in Engineering and Management … , 2025 2025
A Study to Perform Pdf Malware Detection through Document Analysis and Logistic Model Tree Techniques DHM Kiran Pachlasiya POWER SYSTEM TECHNOLOGY(1000-3673) 48 (4), 15 , 2024 2024
Malware Detection Using Machine Learning: A Survey DHM Kiran Pachlasiya Kuwait Research Journal of Education and Literature (KRJEL) 3 (3), 1-13 , 2024 2024
ENHANCING ANDROID MALWARE DETECTION USING MULTI-LAYERED STACKING AND MACHINE LEARNING TECHNIQUES DHM Kiran Pachlasiya International Journal of Advance Research in Science and Engineering 13 (07), 10 , 2024 2024
IOT ENABLED SMART PEN FOR 3D PRINTING K Pachlasiya IN Patent 408608-001 , 2024 2024
Quantum technology for military applications S Nahar, D Pithawa, V Bhardwaj, R Rawat, A Rawat, K Pachlasiya Quantum Computing in Cybersecurity, 313-334 , 2023 2023 Citations: 97
Deep Learning Classifiers for Improving Breast Cancer Detection ACRS Harshita Jain, Kiran Pachlasiya Acta Scientific Applied Physics 3 (Issue 8 August 2023), 4 , 2023 2023
IoT and artificial intelligence techniques for public safety and security V Mahor, R Rawat, A Kumar, B Garg, K Pachlasiya Smart urban computing applications, 111-126 , 2023 2023 Citations: 122
Systematic Literature Review (SLR) on Social Media and the Digital Transformation of Drug R Rawat, V Mahor, M Chouhan, K Pachlasiya, S Telang¹, B Garg Proceedings of International Conference on Network Security and Blockchain … , 2022 2022
Organ Trafficking on the Dark Web—The Data Security and Privacy Concern in Healthcare Systems KP Mukesh Chouhan Romil Rawat,Bhagwati Garg,Vinod Mahor,Shrikant Telang Internet of Healthcare Things: Machine Learning for Security and Privacy … , 2022 2022 Citations: 86
SCNTA R Rawat, B Garg, K Pachlasiya, V Mahor, S Telang, M Chouhan, ... International Journal of Information Technology and Web Engineering 17 (1) , 2022 2022
Modeling of cyber threat analysis and vulnerability in IoT-based healthcare systems during COVID R Rawat, V Mahor, B Garg, M Chouhan, K Pachlasiya, S Telang Lessons from COVID-19, 405-425 , 2022 2022 Citations: 44
SCNTA: Monitoring of network availability and activity for identification of anomalies using machine learning approaches R Rawat, B Garg, K Pachlasiya, V Mahor, S Telang, M Chouhan, ... International Journal of Information Technology and Web Engineering (IJITWE … , 2022 2022 Citations: 78
Analyzing newspaper articles for text-related data for finding vulnerable posts over the internet that are linked to terrorist activities R Rawat, V Mahor, B Garg, S Telang, K Pachlasiya, A Kumar, SK Shukla, ... International Journal of Information Security and Privacy (IJISP) 16 (1), 1-14 , 2022 2022 Citations: 27
Systematic literature review (SLR) on social media and the digital transformation of drug trafficking on darkweb R Rawat, V Mahor, M Chouhan, K Pachlasiya, S Telang, B Garg International conference on network security and blockchain technology, 181-205 , 2022 2022 Citations: 91
Malware inputs detection approach (Tool) based on machine learning [MIDT-SVM] R Rawat, M Chouhan, B Garg, S TELANG, V Mahor, K Pachlasiya Available at SSRN 3915404 , 2021 2021 Citations: 3
Mobile Operating System (Android) Vulnerability Analysis Using Machine Learning V Mahor, K Pachlasiya, B Garg, M Chouhan, S Telang, R Rawat International Conference on Network Security and Blockchain Technology, 159-169 , 2021 2021 Citations: 86
Cyber threat phylogeny assessment and vulnerabilities representation at thermal power station V Mahor, B Garg, S Telang, K Pachlasiya, M Chouhan, R Rawat International Conference on Network Security and Blockchain Technology, 28-39 , 2021 2021 Citations: 80
Automated Techniques for Analyzing Cyber Threat Triggered by Terrorists and Criminals in Anonymous Space KP Shrikant Telang Romil Rawat, Bhagwati Garg, Vinod Mahor, Mukesh Chouhan https://www.elivapress.com/en/book/book-9106824963/ , 2021 2021
MOST CITED SCHOLAR PUBLICATIONS
IoT and artificial intelligence techniques for public safety and security V Mahor, R Rawat, A Kumar, B Garg, K Pachlasiya Smart urban computing applications, 111-126 , 2023 2023.0 Citations: 122
Quantum technology for military applications S Nahar, D Pithawa, V Bhardwaj, R Rawat, A Rawat, K Pachlasiya Quantum Computing in Cybersecurity, 313-334 , 2023 2023.0 Citations: 97
Systematic literature review (SLR) on social media and the digital transformation of drug trafficking on darkweb R Rawat, V Mahor, M Chouhan, K Pachlasiya, S Telang, B Garg International conference on network security and blockchain technology, 181-205 , 2022 2022.0 Citations: 91
Organ Trafficking on the Dark Web—The Data Security and Privacy Concern in Healthcare Systems KP Mukesh Chouhan Romil Rawat,Bhagwati Garg,Vinod Mahor,Shrikant Telang Internet of Healthcare Things: Machine Learning for Security and Privacy … , 2022 2022.0 Citations: 86
Mobile Operating System (Android) Vulnerability Analysis Using Machine Learning V Mahor, K Pachlasiya, B Garg, M Chouhan, S Telang, R Rawat International Conference on Network Security and Blockchain Technology, 159-169 , 2021 2021.0 Citations: 86
Cyber threat phylogeny assessment and vulnerabilities representation at thermal power station V Mahor, B Garg, S Telang, K Pachlasiya, M Chouhan, R Rawat International Conference on Network Security and Blockchain Technology, 28-39 , 2021 2021.0 Citations: 80
SCNTA: Monitoring of network availability and activity for identification of anomalies using machine learning approaches R Rawat, B Garg, K Pachlasiya, V Mahor, S Telang, M Chouhan, ... International Journal of Information Technology and Web Engineering (IJITWE … , 2022 2022.0 Citations: 78
Modeling of cyber threat analysis and vulnerability in IoT-based healthcare systems during COVID R Rawat, V Mahor, B Garg, M Chouhan, K Pachlasiya, S Telang Lessons from COVID-19, 405-425 , 2022 2022.0 Citations: 44
Analyzing newspaper articles for text-related data for finding vulnerable posts over the internet that are linked to terrorist activities R Rawat, V Mahor, B Garg, S Telang, K Pachlasiya, A Kumar, SK Shukla, ... International Journal of Information Security and Privacy (IJISP) 16 (1), 1-14 , 2022 2022.0 Citations: 27
Cyber Threat Exploitation and Growth during COVID-19 Times R Rawat, B Garg, V Mahor, M Chouhan, K Pachlasiya, S Telang Advanced Smart Computing Technologies in Cybersecurity and Forensics, 85-101 , 2021 2021.0 Citations: 10
19 Times R Rawat, B Garg, V Mahor, M Chouhan, K Pachlasiya, G during COVID Advanced Smart Computing Technologies in Cybersecurity and Forensics, 85-101 , 0 Citations: 4
Malware inputs detection approach (Tool) based on machine learning [MIDT-SVM] R Rawat, M Chouhan, B Garg, S TELANG, V Mahor, K Pachlasiya Available at SSRN 3915404 , 2021 2021.0 Citations: 3
Systematic literature Review (SLR) on Social Media and the Digital Transformation of Drug Trafficking on Darkweb (August 12, 2021) R Rawat, V Mahor, A Kumar, S Telang, K Pachlasiya, B Garg, M Chouhan AIBM-2nd International Conference on" Methods and Applications of Artificial … , 2021 2021.0 Citations: 3
Pachlasiya, & Chouhan.(2021) G Rawat, T Mahor Organ trafficking on the dark web—the data security and privacy concern in … , 0 Citations: 2
Mahor.(2021) K Rawat, T Chouhan, G Pachlasiya Systematic literature review (slr) on social media and the digital … , 0 Citations: 2
AI-Driven Flexibility in Next-Generation Communication Systems A Review of Models, Confrontation, and Tomorrow’s Directions SS Kiran Pachlasiya International Journal of Scientific Research in Engineering and Management … , 2025 2025.0
Density Based Smart Traffic Control System Using Canny Edge Detection SR Likhita Devi Ravipati Kiran Pachlasiya International Journal of Scientific Research in Engineering and Management … , 2025 2025.0
A Study to Perform Pdf Malware Detection through Document Analysis and Logistic Model Tree Techniques DHM Kiran Pachlasiya POWER SYSTEM TECHNOLOGY(1000-3673) 48 (4), 15 , 2024 2024.0
Malware Detection Using Machine Learning: A Survey DHM Kiran Pachlasiya Kuwait Research Journal of Education and Literature (KRJEL) 3 (3), 1-13 , 2024 2024.0
ENHANCING ANDROID MALWARE DETECTION USING MULTI-LAYERED STACKING AND MACHINE LEARNING TECHNIQUES DHM Kiran Pachlasiya International Journal of Advance Research in Science and Engineering 13 (07), 10 , 2024 2024.0
